Title: Ride Comfort-Aware Visual Navigation via Self-Supervised Learning

Abstract:

Under shared autonomy, wheelchair users expect vehicles to provide safe and comfortable rides while following users’ high-level navigation plans. To find such a path, vehicles negotiate with different terrains and assess their traversal difficulty. Most prior works model surroundings either through geometric representations or semantic classifications, which do not reflect perceived motion intensity and ride comfort in downstream navigation tasks. We propose to model ride comfort explicitly in traversability analysis using proprioceptive sensing. We develop a self-supervised learning framework to predict traversability costmap from first-person-view images by leveraging vehicle states as training signals. Our approach estimates how the vehicle would “feel” if traversing over based on terrain appearances. We then show our navigation system provides human-preferred ride comfort through robot experiments together with a human evaluation study.

Committee:

Prof. Jean Oh
Prof. Ji Zhang
Prof. Stephen Smith
Tanmay Shankar

Location: Newell-Simon Hall (NSH) 4305

Zoom: https://cmu.zoom.us/j/94936974669?pwd=c3VLVEVTbDhiSXAyZDY5ZndtcjZHdz09

Meeting ID: 949 3697 4669

Passcode: 758557